How to Create a Project Portfolio Dashboard in Google Analytics with AI
Tracking the performance of a single website in Google Analytics is straightforward. But what happens when you’re responsible for a whole portfolio of them? Whether you're a marketing agency managing dozens of client sites, a business with multiple web properties, or a product manager overseeing several different products, getting a simple, high-level view is surprisingly difficult and time-consuming. You need a project portfolio dashboard, and this article will show you how to build one faster than ever using AI.
We'll walk through the common challenges of consolidating data from multiple Google Analytics properties and show you how to bypass them completely by using natural language to build a comprehensive, always-on portfolio dashboard in minutes, not hours.
What is a Project Portfolio Dashboard?
A project portfolio dashboard is a single visual interface that consolidates key performance indicators (KPIs) from multiple, separate projects. In the context of Google Analytics, it’s a report that pulls data from several different GA4 properties and displays it in one place. This gives you a clear bird's-eye view of how all your websites or digital assets are performing collectively and in comparison to each other.
Imagine being able to answer these questions at a glance:
What is the total user traffic across my entire portfolio of websites?
Which website is driving the most conversions this month?
How does the user engagement on Project A compare to Project B and Project C?
Which marketing channel is most effective across all properties combined?
Without a portfolio dashboard, answering these questions involves logging into each GA4 property one by one, manually exporting data, and then stitching it together in a spreadsheet. A portfolio dashboard automates this, giving stakeholders an immediate, high-level understanding of overall performance without getting lost in the weeds of a single account.
The Old Way: The Headache of Manual Data Consolidation
Traditionally, creating a portfolio view in Google Analytics has been a significant barrier for many teams. The methods were either too expensive, too technical, or too slow.
1. The Enterprise Solution: Google Analytics 360 Roll-Up Properties
For a long time, the only "official" way to do this within the GA ecosystem was with Roll-Up Properties, a feature exclusive to the paid Google Analytics 360 suite. This feature automatically aggregates data from multiple source properties into a new, consolidated view. The catch? GA360 comes with a hefty five-figure annual price tag, putting it out of reach for most small to medium-sized businesses and agencies.
2. The DIY Way: Spreadsheet Hell
The most common approach has been the manual export. The workflow usually looks something like this:
Step 1: Log into the first GA4 property.
Step 2: Navigate to the right report and set the date range.
Step 3: Export the data to a CSV or Google Sheet.
Step 4: Repeat steps 1-3 for every single property in your portfolio.
Step 5: Open a master spreadsheet and start the tedious process of copying, pasting, and combining the data from all your exports.
Step 6: Manually build charts and tables to visualize the consolidated data.
This process is not only incredibly boring but also inefficient and error-prone. It can take hours every week just to update the report. Worse, by the time you're finished building it, the data is already out of date.
3. The BI Tool Approach: Looker Studio (and its challenges)
Tools like Google's Looker Studio (formerly Data Studio) offer a more automated solution than spreadsheets. You can connect multiple GA4 properties as data sources and blend them together to create a unified dashboard. While powerful, this approach has a steep learning curve. Setting up data blending, writing calculated field formulas, and designing a clean and effective dashboard requires technical knowledge and a significant time investment to master. It's an improvement over spreadsheets, but it’s still far from an easy, out-of-the-box solution.
The New Way: Building Your Dashboard with AI and Natural Language
Instead of wrestling with data exports or complex BI tools, you can now use AI-powered analytics platforms to build your portfolio dashboard in seconds. Think of these tools as having a data analyst on your team. You simply connect your data sources once, then tell the AI what you want to see using plain English prompts.
The AI handles all the messy backend work for you:
It understands which metrics you're asking for (e.g., "users," "traffic," "conversions").
It knows how to query each connected GA4 property to get the right data.
It automatically aggregates and visualizes that data into the chart or report you requested.
This approach completely eliminates manual work and the technical learning curve. If you can describe the report you need, you can build it.
Step-by-Step: Creating Your Dashboard with Simple Prompts
Building an entire dashboard might sound intimidating, but the process is as simple as having a conversation. You work widget by widget, asking for charts and KPIs one at a time to assemble your custom view.
Step 1: Connect Your Google Analytics Accounts
The first step is always to give the AI access to your data. Modern analytics tools make this painless. Instead of hunting for API keys, you typically just log in with your Google account (a process called OAuth). You can securely connect as many GA4 properties as you manage in just a few clicks. The AI will then have the necessary access to pull your data in real-time.
Step 2: Assemble Your Dashboard with Conversational Prompts
Once connected, you can start building. You don't ask for a "portfolio dashboard" all at once. Instead, you build it piece by piece by asking for individual visualizations.
Let's build a sample dashboard to see how it works:
To start, get the big picture KPIs:
Begin with scorecards that show your portfolio's most important top-level metrics.
"Show me a scorecard with the total number of users across all my Google Analytics properties this month."
"Create a KPI card showing the aggregate conversion rate for all projects in the last 30 days."
Next, compare individual project performance:
Once you have the overall numbers, you'll want to see how each project contributes. Bar charts are great for this.
"Make a bar chart comparing total sessions per Google Analytics property for this quarter."
The AI will generate a chart with a bar for each property you've connected, allowing you to quickly spot top performers and see who might be lagging.
"Create a table that breaks down total users, new users, and conversions by property for the last 7 days."
Then, analyze your aggregated traffic sources:
Understanding where all your traffic is coming from is critical. Ask the AI to combine the channel data from every property.
"Show me a pie chart of my top traffic channels across all projects combined."
This helps you see if your portfolio as a whole relies more on Organic Search, Paid Social, Direct, or other channels, guiding your overall marketing strategy.
Step 3: Ask Follow-Up Questions to Refine Your View
The real power of conversational analytics is the ability to iterate and drill down. Your initial chart might trigger another question. Just ask it.
Spotted a spike in your line chart? Ask: "What caused the traffic spike last Tuesday?"
Want to see the data differently? Ask: "Change that last bar chart to a horizontal bar chart."
Need more detail on a specific channel? Ask: "Filter the traffic table to only show organic and paid search results."
This interactive process allows you to explore your data freely, uncovering insights that would have been buried in spreadsheets.
Beyond Google Analytics: Creating a True Portfolio Command Center
While invaluable, Google Analytics data only tells part of the story. A truly effective project portfolio dashboard often needs to connect website performance to actual business outcomes. This means pulling in data from other platforms.
Your "projects" might involve more than just a website. You might have ad campaigns, sales funnels, and email marketing efforts associated with each one. With an AI analytics tool, you can connect these other systems alongside Google Analytics to build a complete picture:
Ad Platforms (Facebook Ads, Google Ads): How much are you spending to acquire traffic for each project vs. the results you're seeing?
CRMs (Salesforce, HubSpot): Are website visitors turning into qualified leads and closed deals?
E-commerce Platforms (Shopify): Which websites are driving the most revenue for the business?
Once these sources are connected, you can ask even more powerful questions:
"Show me a combo chart comparing Google Ads spend and Shopify revenue for Project A versus Project B this month."
"Build a report that shows GA4 users versus new leads created in HubSpot by property for the last 30 days."
This is where an AI-driven dashboard goes from a simple reporting tool to a true command center for your entire marketing and sales operation, centralizing all your client or project data into a single, cohesive view.
Final Thoughts
Managing a portfolio of projects doesn't have to mean spending half your week stuck in reporting mode. By leveraging AI, you can move away from tedious manual exports and complex BI configurations and create a consolidated project portfolio dashboard that provides a real-time, high-level view of performance across all your web properties.
At Graphed, we turn this entire process into a simple, 30-second conversation. You connect your Google Analytics accounts, ad platforms, and CRM with a few clicks, then just describe the charts, tables, and KPIs you want to see. We automatically build a live, interactive dashboard that gives you the cross-platform insights you need to make better decisions faster, liberating you and your team from the drudgery of manual reporting.